Role of Nitric Oxide in Shiga Toxin-2-Induced Premature Delivery of Dead Fetuses in Rats

Shiga toxin-producing Escherichia coli (STEC) infections could be one of the causes of fetal morbimortality in pregnant women. The main virulence factors of STEC are Shiga toxin type 1 and/or 2 (Stx1, Stx2). We previously reported that intraperitoneal (i.p.) injection of rats in the late stage of pregnancy with culture supernatant from recombinant E. coli expressing Stx2 and containing lipopolysaccharide (LPS) induces premature delivery of dead fetuses. It has been reported that LPS may combine with Stx2 to facilitate vascular injury, which may in turn lead to an overproduction of nitric oxide (NO). The aim of this study was to evaluate whether NO is involved in the effects of Stx2 on pregnancy. Pregnant rats were i.p. injected with culture supernatant from recombinant E. coli containing Stx2 and LPS (sStx2) on day 15 of gestation. In addition, some rats were injected with aminoguanidine (AG), an inducible isoform inhibitor of NO synthase (iNOS), 24 h before and 4 h after sStx2 injection. NO production was measured by NOS activity and iNOS expression by Western blot analysis. A significant increase in NO production and a high iNOS expression was observed in placental tissues from rats injected with sStx2 containing 0.7 ng and 2 ng Stx2/g body weight and killed 12 h after injection. AG caused a significant reduction of sStx2 effects on the feto-maternal unit, but did not prevent premature delivery. Placental tissues from rats treated with AG and sStx2 presented normal histology that was indistinguishable from the controls. Our results reveal that Stx2-induced placental damage and fetus mortality is mediated by an increase in NO production and that AG is able to completely reverse the Stx2 damages in placental tissues, but not to prevent premature delivery, thus suggesting other mechanisms not yet determined could be involved

Structural optimization with design constraints on peak responses to temporally correlated quasi-static load processes

[[abstract]]Structural optimization has become a widely used tool for various applications due to its capability of providing design freedom and promise to efficient structures. Current optimization methods are usually utilized for producing optimal structural systems subjected to design constraints under definite static or dynamic load distributions. However, engineering structures may experience randomly fluctuating loads in different physical environments. In this paper, a methodology of structural optimization with constraints on peak system responses to temporally correlated quasi-static load processes is developed. The proposed methodology provides an algorithm for generating structures of the optimal designs with constraints on their extreme responses to such environmental load sequences which have correlation features in the time domain. The computational results confirm that material distributions of optimized structures with peak response constraints highly depend on correlation levels of quasi-static load distributions under stationary processes. Furthermore, conventional optimization of structures in statics with displacement constraints is also compared with the reported optimum material distributions with peak response constraints under correlated load sequences. In consequence, the developed methodology provides a powerful tool of structural designs under stationary processes of temporally correlated loads having very low frequencies for fundamental engineering structures and further multidisciplinary mechanics researches.[[notice]]補正完

Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs.

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior